A Structural Equation Modeling Approach to Evaluating Library Personnel Intention to Adopt Big Data Technology in Nigerian Academic Libraries. Issue 4 (29th October 2021) - Owolabi, Kehinde Abayomi; Adeleke, Olateju Abayomi; Tella, Adeyinka; Mudasiru, Yusuf Abiodun
Abstract: Big data technology has gained prominence among academia and organizations around the world. As libraries continue to receive data from different sources like physical and electronic books and journals, recordings, maps, field trip documentation, and a host of others, big data technology becomes essential in managing all these datasets. However, much is unknown about its adoption among library personnel in academic libraries in Nigerian tertiary institutions. Thus, the research examined librarians' behavioral intentions to adopt big data technology in Nigerian universities. Data were collected through a questionnaire distributed to 317 library personnel. The hypothesized relationships in the model were tested using the Covariance-Based Structural Equation Modeling (CB-SEM). The results show that performance expectancy, social influence, and facilitating conditions influence behavioral intention to adopt big data technology. Contrarily, effort expectancy does not influence behavioral intention to adopt big data technology. With 50% of the variance in library personnel's intention to use big data technology explained by this model, it could help determine factors that could influence big data technology acceptance and use in academic libraries.